AIMC Topic: Carbon Footprint

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Carbon Reporting Practices in the NHS: Emissions and Omissions Relating to Artificial Intelligence.

Journal of medical Internet research
Artificial intelligence (AI) is being rolled out across the UK National Health Service (NHS) to improve efficiency; yet, its carbon footprint is largely invisible within mandatory Green Plan reporting. This work shows where NHS carbon reporting omits...

Carbon footprint of food production: a systematic review and meta-analysis.

Scientific reports
In the face of the urgent climate crisis, food production is a significant contributor to greenhouse gas emissions (GHG). We analyzed 118 life-cycle assessment (LCA) studies on GHG emissions of food production, considering LCA methods, life cycle pha...

Optimization of carbon footprint management model of electric power enterprises based on artificial intelligence.

PloS one
This study intends to optimize the carbon footprint management model of power enterprises through artificial intelligence (AI) technology to help the scientific formulation of carbon emission reduction strategies. Firstly, a carbon footprint calculat...

Effective carbon footprint assessment strategy in fly ash geopolymer concrete based on adaptive boosting learning techniques.

Environmental research
In light of the growing need to mitigate climate change impacts, this study presents an innovative methodology combining ensemble machine learning with experimental data to accurately predict the carbon dioxide footprint (CO-FP) of fly ash geopolymer...

Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future.

Diagnostic and interventional imaging
The rapid advancement of artificial intelligence (AI) in healthcare has revolutionized the industry, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. However, the increasing adoption of AI systems also raise...

Environmental Impacts of Machine Learning Applications in Protein Science.

Cold Spring Harbor perspectives in biology
Computing tools and machine learning models play an increasingly important role in biology and are now an essential part of discoveries in protein science. The growing energy needs of modern algorithms have raised concerns in the computational scienc...

Mitigating carbon footprint for knowledge distillation based deep learning model compression.

PloS one
Deep learning techniques have recently demonstrated remarkable success in numerous domains. Typically, the success of these deep learning models is measured in terms of performance metrics such as accuracy and mean average precision (mAP). Generally,...

Method and evaluations of the effective gain of artificial intelligence models for reducing CO2 emissions.

Journal of environmental management
Nowadays, there is an increasing use of digital technologies and Artificial Intelligence (AI) such as Machine Learning (ML) models that leverage data to optimize the performances of systems in almost all activity sectors, including ML models for opti...

Using Deep Learning to Fill Data Gaps in Environmental Footprint Accounting.

Environmental science & technology
Environmental footprint accounting relies on economic input-output (IO) models. However, the compilation of IO models is costly and time-consuming, leading to the lack of timely detailed IO data. The RAS method is traditionally used to predict future...